Sentiment Analysis and Recurrent Radial Basis Function Network for Bitcoin Price Prediction

The value of Bitcoin, and more generally the world of 'crypto-currencies', has always been characterized by its volatile and unpredictable nature. The value of these assets, indeed, is established independently by the parties participating in the exchanges and cannot be influenced by any regulatory organ or central authority. In recent years, thanks to the Web, a world of virtual communities has been created around the Bitcoin phenomenon, whose discussions directly or indirectly influence the price of this digital asset. Through appropriate analysis of Big Data from the main Social Networks, it is possible to identify correlations between the general sentiment of the community and the value of the currency exchanged. The purpose, therefore, of this work is to go and identify the influences of the Bitcoin market through the analysis of the opinions and feelings of the large communities belonging to the Social Network Reddit to try to make short-term predictions about the price of the currency. Tools based on Machine Learning and Deep Learning techniques can help to identify these phenomena with a high degree of accuracy. The results show how an approach based on Recurrent Radial Basis Function Network (RRBFN) is effective to perform the prediction of a given digital asset starting from the analysis of sentiments contained in online discussions.